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Control Strategies for Daylight and Artificial Lighting in Office Buildings—A Bibliometrically Assisted Review

Author

Listed:
  • Daniel Plörer

    (Unit of Energy Efficient Building, University of Innsbruck, A-6020 Innsbruck, Austria)

  • Sascha Hammes

    (Unit of Energy Efficient Building, University of Innsbruck, A-6020 Innsbruck, Austria
    Bartenbach GmbH, A-6071 Aldrans, Austria)

  • Martin Hauer

    (Unit of Energy Efficient Building, University of Innsbruck, A-6020 Innsbruck, Austria
    Bartenbach GmbH, A-6071 Aldrans, Austria)

  • Vincent van Karsbergen

    (Unit of Energy Efficient Building, University of Innsbruck, A-6020 Innsbruck, Austria)

  • Rainer Pfluger

    (Unit of Energy Efficient Building, University of Innsbruck, A-6020 Innsbruck, Austria)

Abstract

A significant proportion of the total energy consumption in office buildings is attributable to lighting. Enhancements in energy efficiency are currently achieved through strategies to reduce artificial lighting by intelligent daylight utilization. Control strategies in the field of daylighting and artificial lighting are mostly rule-based and focus either on comfort aspects or energy objectives. This paper aims to provide an overview of published scientific literature on enhanced control strategies, in which new control approaches are critically analysed regarding the fulfilment of energy efficiency targets and comfort criteria simultaneously. For this purpose, subject-specific review articles from the period between 2015 and 2020 and their research sources from as far back as 1978 are analysed. Results show clearly that building controls increasingly need to address multiple trades to achieve a maximum improvement in user comfort and energy efficiency. User acceptance can be highlighted as a decisive factor in achieving targeted system efficiencies, which are highly determined by the ability of active user interaction in the automatic control system. The future trend is moving towards decentralized control concepts including appropriate occupancy detection and space zoning. Simulation-based controls and learning systems are identified as appropriate methods that can play a decisive role in reducing building energy demand through integral control concepts.

Suggested Citation

  • Daniel Plörer & Sascha Hammes & Martin Hauer & Vincent van Karsbergen & Rainer Pfluger, 2021. "Control Strategies for Daylight and Artificial Lighting in Office Buildings—A Bibliometrically Assisted Review," Energies, MDPI, vol. 14(13), pages 1-18, June.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:13:p:3852-:d:582761
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    References listed on IDEAS

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    Cited by:

    1. Ritesh Wankhade & Giovanni Pernigotto & Michele Larcher, 2023. "A Literature Review on Methods and Metrics for the Analysis of Outdoor Air Displacement Conditions in the Urban Environment," Energies, MDPI, vol. 16(6), pages 1-31, March.
    2. V. S. K. V. Harish & Arun Kumar & Tabish Alam & Paolo Blecich, 2021. "Assessment of State-Space Building Energy System Models in Terms of Stability and Controllability," Sustainability, MDPI, vol. 13(21), pages 1-26, October.
    3. Krzysztof Górecki & Przemysław Ptak & Sylwia Wnuczko, 2022. "The Embedded System to Control the Illuminance of an Office Workplace with LED Light Sources," Energies, MDPI, vol. 15(7), pages 1-20, March.

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